Social media feeds are often filled with skydiving clips, trips to Paris, and other unusual events — not because algorithms demand it, but because people are naturally drawn to share the rare and exciting. New research from Virginia Tech argues that this human tendency, not just the platform’s code, is what distorts what users see online.
The study, published in MIS Quarterly, introduces a concept called “rareness bias diffusion.” It describes how users constantly see unique events, overestimate how often those events happen, and then feel compelled to share their own uncommon experiences. The result is a feedback loop where ordinary life disappears from view.
“They think everyone else is traveling to Paris or doing something exciting, while they are just sitting at home doing mundane things,” said Alice Jang, an assistant professor in the Pamplin College of Business. “It makes people feel like their lives are falling short, when in reality, everyone is mostly doing mundane things — they just only post the exciting parts.”
Jang and co-author Viswanath Venkatesh, chair of business information technology at Virginia Tech, conducted six experiments to understand how people choose what to share. In one, participants were shown fictional scenarios of a dystopian city under attack by monsters. The scenarios were presented unevenly — some more than others. People consistently chose to share the scenario they had seen the least, reinforcing the pull toward novelty.
They then built a simulated mock network of thousands of users and unique content to test the effect at scale. The pattern held: rare information spreads widely because humans seek variety and perceive uncommon events as more common than they really are.
Related: What are the important tips that you need to know for overcoming childhood obesity?
This is not just about algorithms. According to the research, the distortion on social media is “not totally driven by the algorithm. Instead, it comes from ordinary human biases that social media compounds into a pattern where rare information gets shared more often.”
The tendency to overlook the ordinary happens because of users’ perception bias and their motivation to seek variety in what they see and share, the study notes.
Jang is blunt about the limits of intervention. “There is a bias that we simply cannot fix. It’s impossible to fix,” she said. “A lot of the prior literature just disregards this fact and assumes that people are rational.” Venkatesh added that awareness alone might help: “Yes, it’s a bias but when people know this, they could perhaps know that what we are seeing on social media is others’ highlight reel and not the day-to-day life. This may reduce harmful negative impacts on oneself.”
The research challenges the common assumption that social media’s problems are primarily algorithmic. Instead, it points to a deeper human baseline that platforms cannot fully correct. That leaves the responsibility on users to recognize that their feeds are packed with exciting content because of what they — and everyone else — choose to engage with. Having that knowledge allows users to better protect themselves from a false reality. New drug could shield hearts in a different medical context, but here the focus remains on digital perception.